Orphanet

There are more than 6000 known Rare Diseases (RDs), which are often multi-systemic, and about 200 rare cancers (RC) which are the RD of oncology. The knowledge and understanding of rare diseases and rare cancers is limited because of their rarity. The European Health Data Space (EHDS) is a set of regulations, standards and guidelines that aim to empower individuals to access and control their personal health data. Electronic Health Records (EHRs) form the basis for primary data sharing and information exchange in the EHDS, instrumental for improving the quality and safety of patient care, while supporting research, innovation, and policy-making. Patient Summary is one of the primary health data categories mandated by the EHDS. This paper reviews essential data elements for RD and RC patient summaries. Starting from typical use cases for planned and unplanned care, this paper proposes data element extensions for patient summaries that address the needs of RD and RC patients, bridging primary and secondary use of data.

The European Joint Programme on Rare Diseases (EJP RD) represents a significant step forward in the rare diseases research ecosystem, integrating over 130 institutions from 35 countries. It focuses on streamlining the process from basic research to clinical application, fostering collaboration at an international scale, and emphasizing patient engagement. The initiative has funded numerous projects across various medical domains, developed the Rare Diseases Virtual Platform, and significantly impacted the rare disease landscape through training, project mentoring, and innovative methodology developments. Expanding beyond, EJP RD collaborates with various initiatives to optimize resource use and is evolving into the European Rare Diseases Research Alliance, aiming to accelerate diagnostics, develop innovative therapies, and assess the rare disease burden to inform policy decisions.

The prolactin receptor gene (PRLR) may contribute to polycystic ovarian syndrome (PCOS) since it plays important roles in physiological ovarian functions. PRLR-knockout mice have irregular cycles and subfertility and variants in or around the PRLR gene were associated in humans with female testosterone levels and recurrent miscarriage. We tested 40 variants in the PRLR gene in 212 Italian families phenotyped by type 2 diabetes (T2D) and PCOS and found two intronic PRLR-variants (rs13436213 and rs1604428) significantly linked to and/or associated with the risk of PCOS. This is the first study to report PRLR as a novel risk gene in PCOS. Functional studies are needed to confirm these results.

Polycystic ovarian syndrome (PCOS) is a complex heterogeneous condition that affects women of reproductive age, conferring increased cardiovascular morbidity and mortality. The syndrome is characterized by oligomenorrhea, hyperandrogenism, and/or polycystic ovaries and is often associated with obesity and type 2 diabetes. Individuals are predisposed to PCOS by environmental factors and risk variants in genes mostly involved in ovarian steroidogenesis and/or insulin resistance. Genetic risk factors have been identified by both familial and genome-wide (GW) association studies. However, most genetic components are still unknown and missing heritability needs to be elucidated. To learn more about the genetic determinants of PCOS, we performed a GW study in genetically highly homogeneous peninsular families. We conducted the first GW-linkage and linkage disequilibrium (i.e., linkage + association) study in Italian families with PCOS. We identified several novel risk variants, genes, and pathways potentially implicated in the pathogenesis of PCOS. Specifically, we detected 79 novel variants with significant GW-linkage and/or -association with PCOS across 4 inheritance models (p < 0.00005), of which 50 variants were within 45 novel PCOS-risk genes. This is the first GW-linkage and linkage disequilibrium study performed in peninsular Italian families and reporting novel genes in PCOS.

BackgroundCongenital myasthenic syndromes (CMS) are a heterogeneous group of inherited neuromuscular disorders sharing the common feature of fatigable weakness due to defective neuromuscular transmission. Despite rapidly increasing knowledge about the genetic origins, specific features and potential treatments for the known CMS entities, the lack of standardized classification at the most granular level has hindered the implementation of computer-based systems for knowledge capture and reuse. Where individual clinical or genetic entities do not exist in disease coding systems, they are often invisible in clinical records and inadequately annotated in information systems, and features that apply to one disease but not another cannot be adequately differentiated.ResultsWe created a detailed classification of all CMS disease entities suitable for use in clinical and genetic databases and decision support systems. To avoid conflict with existing coding systems as well as with expert-defined group-level classifications, we developed a collaboration with the Orphanet nomenclature for rare diseases, creating a clinically understandable name for each entity and placing it within a logical hierarchy that paves the way towards computer-aided clinical systems and improved knowledge bases for CMS that can adequately differentiate between types and ascribe relevant expert knowledge to each.ConclusionsWe suggest that data science approaches can be used effectively in the clinical domain in a way that does not disrupt preexisting expert classification and that enhances the utility of existing coding systems. Our classification provides a comprehensive view of the individual CMS entities in a manner that supports differential diagnosis and understanding of the range and heterogeneity of the disease but that also enables robust computational coding and hierarchy for machine-readability. It can be extended as required in the light of future scientific advances, but already provides the starting point for the creation of FAIR (Findable, Accessible, Interoperable and Reusable) knowledge bases of data on the congenital myasthenic syndromes.

BackgroundRandomised clinical trials are key to advancing medical knowledge and to enhancing patient care, but major barriers to their conduct exist. The present paper presents some of these barriers.MethodsWe performed systematic literature searches and internal European Clinical Research Infrastructure Network (ECRIN) communications during face-to-face meetings and telephone conferences from 2013 to 2017 within the context of the ECRIN Integrating Activity (ECRIN-IA) project.ResultsThe following barriers to randomised clinical trials were identified: inadequate knowledge of clinical research and trial methodology; lack of funding; excessive monitoring; restrictive privacy law and lack of transparency; complex regulatory requirements; and inadequate infrastructures. There is a need for more pragmatic randomised clinical trials conducted with low risks of systematic and random errors, and multinational cooperation is essential.ConclusionsThe present paper presents major barriers to randomised clinical trials. It also underlines the value of using a pan-European-distributed infrastructure to help investigators overcome barriers for multi-country trials in any disease area.

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their “diagnostic odyssey,” improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.